1. Applying data visualisation to the
analytics process
Casper Blicher Olsen

2. Let’s go back in time
(The traveling industry)

3. Wright brothers 1900’s
Source:gizmodo.com

4. A lot has changed
Source:gizmodo.com

5. Boeing during the 70’s
Source:gizmodo.com

6. Boeing now
Source:boeing.com

7. Let’s go back in time
(Data Visualizations)

8. Napoleon's disastrous Russian campaign of 1812
Charles Joseph Minard (Paris, 1969)
Charles Joseph Minard
•
Lived 1781–1870
!
•
French civil engineer
•
Information graphics
pioneer
•
Known for the graphical
visualization on the left
(also know as):
“Carte figurative des
pertes successives en
hommes de l'Armée
Française dans la
campagne de Russie
1812-1813”

9. World immigration during 1858
Charles Joseph Minard (Paris, 1962)
Charles Joseph Minard
•
Lived 1781–1870
!
•
French civil engineer
•
Information graphics
pioneer

10. Flow visualisations (2014)
Google Analytics
Google Analytics
•
Graphical representation
of visitors’ flow
•
Nodes are automatically
clustered according to an
intelligence algorithm that
groups together the most
likely visitor flow through
a site.
!
•
Option to drill down into
any node.

11. It (officially) started in 1919
Worlds first book on informations graphics
Get the book here: http://goo.gl/mI7Rzv

12. It (officially) started in 1919
Worlds first book on informations graphics
Get the book here: http://goo.gl/mI7Rzv

13. It (officially) started in 1919
Worlds first book on informations graphics
Get the book here: http://goo.gl/mI7Rzv

14. Warning: do not try this at home…
…or at work!

15. It (officially) started in 1919
Worlds first book presenting a PIE CHART!
Get the book here: http://goo.gl/mI7Rzv

16. It’s the pie chart!
and the truth about it

17. Don’t be a “Pie Charter”
Seriously–don’t!
Source: Urbandictionary

18. The Pie Chart
Round, tasty and full of colours
The reason you should avoid the
use of pie charts…
Source: truefacts.dk

19. The truth about pie charts
before you can break the rules, you need to know them first
Positive
•
Simple share of total.
Negative
•
Whenever there is similarity in the
information available, a pie chart is not
•
Charts are a way to take information
the right chart to use.
and make it more understandable.
•
Whenever there are multiple (3 or
more) different points of data, a pie
chart is not the right chart to use.
•
Pie charts are very easy to abuse.
•
A pie chart is not the right chart to use
if you need to label each percent.

20. World's most accurate pie chart
True story

21. A misleading data visualization
that lead to a disaster
(Space Shuttle Challenger, 1986)

22. Space Shuttle Challenger and the O-ring failure
United States, 1986

23. Space Shuttle Challenger and the O-ring failure
United States, 1986

24. Space Shuttle Challenger and the O-ring failure
United States, 1986

25. Space Shuttle Challenger and the O-ring failure
United States, 1986

26. Space Shuttle Challenger and the O-ring failure
United States, 1986

27. Space Shuttle Challenger and the O-ring failure
United States, 1986
The outcome
!
•
Challenger was destroyed at
11:39:13 am Eastern Standard
Time on January 28, 1986.
•
Seven crew members were killed
!
•
A two-and-a-half year grounding
of the NASA shuttle fleet.

28. Space Shuttle Challenger and the O-ring failure
United States, 1986
Edward Tufte (1942-)
!
•
American statistician and professor emeritus of political
science, statistics, and computer science at Yale University.
!
•
Pioneer in the field of data visualisation
!
•
Books
Tufte also invented sparklines

29. Space Shuttle Challenger and the O-ring failure
United States, 1986

30. Space Shuttle Challenger and the O-ring failure
United States, 1986
Edward Tufte's advice on sharing information
!
1. The most effective way of presenting information in a technical setting, is by
distributing a brief written report that can be read by all participants in the
first 5 to 10 minutes of the meeting.
2. The rest of the meeting is devoted to discussion and debate.

31. Aligning data visualisation to
your analytics processes

32. The definition of visual analytics
From data to visuals to action
Visual analytics is the representation and presentation
of data that EXPLOITS OUR VISUAL PERCEPTION
ABILITIES in order to AMPLIFY COGNITION.
- Andy Kirk, author of “Data Visualisation: a successful design process”

33. The visual sense is our dominating sense
From data to visuals to action
Source: astro.ku.dk/lys/synet.html

34. The core principals of data visualization
From data to visuals to action
What this means…

35. The core principals of data visualization
The visual elements

36. The core principals of data visualization
From data to visuals to action

37. The core principals of data visualization
From data to visuals to action

38. The core principals of data visualization
From data to visuals to action

39. How we THINK we’re using visual analytics
Chuck Norris style

40. …but the truth is something els!
And much more boring.

41. Visual Analytics Maturity Framework
Getting the data
Technology-centric,
engineering-oriented
Report
Store
Integrate
Convert
Clean
Collect
General Level
Inspired by the work of Stephen Few

42. Visual Analytics Maturity Framework
Going from data to visuals
Human-centric,
design-oriented
Predict
Monitor
Communicate
Technology-centric,
engineering-oriented
Analyse
Explore
Report
Store
Integrate
Convert
Clean
Collect
General Level
Inspired by the work of Stephen Few

43. Visual Analytics Maturity Framework
Making visual analytics part of the organisation
Business-centric,
changing behaviour
Transform
Human-centric,
design-oriented
Embed
Scale
Predict
Monitor
Communicate
Technology-centric,
engineering-oriented
Analyse
Explore
Report
Store
Integrate
Convert
Clean
Collect
General Level
CXO Level
Inspired by the work of Stephen Few

44. Takeaways

45. Key takeaways
Something to take home
Something to think about
• What question do you want to answer?
!
• Is this the best way to answer this question?
!
• Does the visualisation add value to the business?
• Are labels, titles and legends effective?
!
• Does the visualisation apply visual best practices?
!
• Is the visualisation right for the receiver / audience?
Taken from Sasha Pasulka, Senior Manager, Product Marketing, Tableau.

46. Stop guessing, just have a look below
Chart Suggestions - A Though-Starter
Variable Width
Column Chart
Table or Table with
Embedded Charts
Bar Chart
Column Chart
Circular Area Chart
Line Chart
Column Chart
Line Chart
Column Histogram
Scatter Chart
Line Histogram
Bubble Chart
Scatter Chart
3D Area Chart
Stacked 100%
Column Chart
Stacked
Column Chart
Stacked 100%
Area Chart
Stacked Area Chart
Pie Chart
Waterfall Chart
Source: http://www.extremepresentation.com/uploads/documents/choosing_a_good_chart.pdf
Stacked 100% Column Chart
with Subcomponents

47. Key takeaways
Helpful resources
Recommended readings for my infographics and visualisation:
!
Akeley, K. & Hanrahan, P. (2001). Real-Time Graphics Architecture. Retrieved November 2, 2013 from
www.graphics.stanford.edu_courses_cs448a-01-fall_lectures_lecture_renderman.2up.pdf.gz
!
Arthur, W.B. (1989). Competing technologies, increasing returns, and lock-in by historical events. Economic Journal 97: 642–665.
!
Charles Joseph Minard. (n.d.). In Wikipedia. Retrieved November 4, 2013 from http://en.wikipedia.org/wiki/
Charles_Joseph_Minard
!
Clair, C.L. (2012). BIG DATA, ANALYTICS, AND HOSPITAL READMISSION RATES. Retrieved November 1,
2013 from http://blogs.forrester.com/craig_le_clair/12-03-18-big_data_analytics_and_hospital _readmission_rates
!
Gualtieri, M. (2013). The Forrester Wave™: Big Data Predictive Analytics Solutions, Q1 2013. Retrieved
November 3, 2013 from http://www.forrester.com/pimages/rws/reprints/document/85601/oid/ 1-KWYFVB
!
VizWiz (2013). Retrieved November 1, 2013 from http://vizwiz.blogspot.dk/p/about-me.html
Few, S. C. (2012). Show Me the Numbers: Designing Tables and Graphs to Enlighten. Burlingame, CA:
Analytics Press.
!
Other awesome stuff: http://www.thefunctionalart.com/2012/10/recommended-readings-for-infographics.html
!

48. Key takeaways
Helpful resources
Recommended readings for my infographics and visualisation:
!
Akeley, K. & Hanrahan, P. (2001). Real-Time Graphics Architecture. Retrieved November 2, 2013 from
www.graphics.stanford.edu_courses_cs448a-01-fall_lectures_lecture_renderman.2up.pdf.gz
!
Arthur, W.B. (1989). Competing technologies, increasing returns, and lock-in by historical events. Economic Journal 97: 642–665.
!
Charles Joseph Minard. (n.d.). In Wikipedia. Retrieved November 4, 2013 from http://en.wikipedia.org/wiki/
Charles_Joseph_Minard
!
Clair, C.L. (2012). BIG DATA, ANALYTICS, AND HOSPITAL READMISSION RATES. Retrieved November 1,
2013 from http://blogs.forrester.com/craig_le_clair/12-03-18-big_data_analytics_and_hospital _readmission_rates
!
Gualtieri, M. (2013). The Forrester Wave™: Big Data Predictive Analytics Solutions, Q1 2013. Retrieved
November 3, 2013 from http://www.forrester.com/pimages/rws/reprints/document/85601/oid/ 1-KWYFVB
!
VizWiz (2013). Retrieved November 1, 2013 from http://vizwiz.blogspot.dk/p/about-me.html
Few, S. C. (2012). Show Me the Numbers: Designing Tables and Graphs to Enlighten. Burlingame, CA:
Analytics Press.
!
Other awesome stuff: http://www.thefunctionalart.com/2012/10/recommended-readings-for-infographics.html
!
Doyle, A., C. (2003). The Complete Sherlock Holmes: Vol. 1. New York: NY. Barnes & Noble Classics.

49. Wise words from Sherlock Holms
Sir Arthur Conan Doyle’s book (2003)
It is of the highest importance in the art of detection
to be able to recognise, out of a number of facts, which
are incidental and which vital.
Otherwise your energy and attention must be
dissipated instead of being concentrated.
- Sherlock Holm, Private Detective

50. Questions?

51. CASPER BLICHER OLSEN
Digital Analytics & Insights Lead
Mail:
casper@iihnordic.com
Cell:
+45 6 1 3 1 40 07
Office: +45 70 20 29 1 9
IIH Nordic A/S, Lille Strandstraede 6
1254 Copenhagen K, Denmark
www.iihnordic.com
Denmark . Norway . Sweden
Thank you